Articles | Volume 13, issue 3
https://doi.org/10.5194/esd-13-1289-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-13-1289-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Sep 2022
Research article |
| 06 Sep 2022
| 06 Sep 2022
Combining machine learning and SMILEs to classify, better understand, and project changes in ENSO events
The Ocean in the Earth System, Max Planck Institute for Meteorology, Hamburg, Germany
Cooperative Institute for Research in Environmental Sciences (CIRES) and Department of Atmospheric and Oceanic Sciences (ATOC), University of Colorado at Boulder, Boulder, CO 80309, USA
Thibault P. Tabarin
independent researcher: Boulder, CO 80303, USA
Sebastian Milinski
The Ocean in the Earth System, Max Planck Institute for Meteorology, Hamburg, Germany
Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO 80307, USA
Cooperative Programs for the Advancement of Earth System Science, University Corporation for Atmospheric Research, Boulder, CO 80307, USA
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Iris Elisabeth de Vries, Sebastian Sippel, Angeline Greene Pendergrass, and Reto Knutti
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Alizée Chemison, Dimitri Defrance, Gilles Ramstein, and Cyril Caminade
Earth Syst. Dynam., 13, 1259–1287, https://doi.org/10.5194/esd-13-1259-2022, https://doi.org/10.5194/esd-13-1259-2022, 2022
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We study the impact of a rapid melting of the ice sheets on monsoon systems during the 21st century. The impact of a partial Antarctica melting is moderate. Conversely, Greenland melting slows down the oceanic Atlantic circulation and changes winds, temperature and pressure patterns, resulting in a southward shift of the tropical rain belt over Africa and America. The seasonality, duration and intensity of rainfall events are affected, with potential severe impacts on vulnerable populations.
Mari R. Tye, Katherine Dagon, Maria J. Molina, Jadwiga H. Richter, Daniele Visioni, Ben Kravitz, and Simone Tilmes
Earth Syst. Dynam., 13, 1233–1257, https://doi.org/10.5194/esd-13-1233-2022, https://doi.org/10.5194/esd-13-1233-2022, 2022
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Miriam D'Errico, Flavio Pons, Pascal Yiou, Soulivanh Tao, Cesare Nardini, Frank Lunkeit, and Davide Faranda
Earth Syst. Dynam., 13, 961–992, https://doi.org/10.5194/esd-13-961-2022, https://doi.org/10.5194/esd-13-961-2022, 2022
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Climate change is already affecting weather extremes. In a warming climate, we will expect the cold spells to decrease in frequency and intensity. Our analysis shows that the frequency of circulation patterns leading to snowy cold-spell events over Italy will not decrease under business-as-usual emission scenarios, although the associated events may not lead to cold conditions in the warmer scenarios.
Charles D. Koven, Vivek K. Arora, Patricia Cadule, Rosie A. Fisher, Chris D. Jones, David M. Lawrence, Jared Lewis, Keith Lindsay, Sabine Mathesius, Malte Meinshausen, Michael Mills, Zebedee Nicholls, Benjamin M. Sanderson, Roland Séférian, Neil C. Swart, William R. Wieder, and Kirsten Zickfeld
Earth Syst. Dynam., 13, 885–909, https://doi.org/10.5194/esd-13-885-2022, https://doi.org/10.5194/esd-13-885-2022, 2022
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We explore the long-term dynamics of Earth's climate and carbon cycles under a pair of contrasting scenarios to the year 2300 using six models that include both climate and carbon cycle dynamics. One scenario assumes very high emissions, while the second assumes a peak in emissions, followed by rapid declines to net negative emissions. We show that the models generally agree that warming is roughly proportional to carbon emissions but that many other aspects of the model projections differ.
Matthias Gröger, Christian Dieterich, Cyril Dutheil, H. E. Markus Meier, and Dmitry V. Sein
Earth Syst. Dynam., 13, 613–631, https://doi.org/10.5194/esd-13-613-2022, https://doi.org/10.5194/esd-13-613-2022, 2022
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Atmospheric rivers transport high amounts of water from subtropical regions to Europe. They are an important driver of heavy precipitation and flooding. Their response to a warmer future climate in Europe has so far been assessed only by global climate models. In this study, we apply for the first time a high-resolution regional climate model that allow to better resolve and understand the fate of atmospheric rivers over Europe.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
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Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Josep Cos, Francisco Doblas-Reyes, Martin Jury, Raül Marcos, Pierre-Antoine Bretonnière, and Margarida Samsó
Earth Syst. Dynam., 13, 321–340, https://doi.org/10.5194/esd-13-321-2022, https://doi.org/10.5194/esd-13-321-2022, 2022
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The Mediterranean has been identified as being more affected by climate change than other regions. We find that amplified warming during summer and annual precipitation declines are expected for the 21st century and that the magnitude of the changes will mainly depend on greenhouse gas emissions. By applying a method giving more importance to models with greater performance and independence, we find that the differences between the last two community modelling efforts are reduced in the region.
Alba de la Vara, Iván M. Parras-Berrocal, Alfredo Izquierdo, Dmitry V. Sein, and William Cabos
Earth Syst. Dynam., 13, 303–319, https://doi.org/10.5194/esd-13-303-2022, https://doi.org/10.5194/esd-13-303-2022, 2022
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We study with the regionally coupled climate model ROM the impact of climate change on the Tyrrhenian Sea circulation, as well as the possible mechanisms and consequences in the NW Mediterranean Sea. Our results show a shift towards the summer circulation pattern by the end of the century. Also, water flowing via the Corsica Channel is more stratified and smaller in volume. Both factors may contribute to the interruption of deep water formation in the Gulf of Lions in the future.
H. E. Markus Meier, Christian Dieterich, Matthias Gröger, Cyril Dutheil, Florian Börgel, Kseniia Safonova, Ole B. Christensen, and Erik Kjellström
Earth Syst. Dynam., 13, 159–199, https://doi.org/10.5194/esd-13-159-2022, https://doi.org/10.5194/esd-13-159-2022, 2022
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In addition to environmental pressures such as eutrophication, overfishing and contaminants, climate change is believed to have an important impact on the marine environment in the future, and marine management should consider the related risks. Hence, we have compared and assessed available scenario simulations for the Baltic Sea and found considerable uncertainties of the projections caused by the underlying assumptions and model biases, in particular for the water and biogeochemical cycles.
Keith B. Rodgers, Sun-Seon Lee, Nan Rosenbloom, Axel Timmermann, Gokhan Danabasoglu, Clara Deser, Jim Edwards, Ji-Eun Kim, Isla R. Simpson, Karl Stein, Malte F. Stuecker, Ryohei Yamaguchi, Tamás Bódai, Eui-Seok Chung, Lei Huang, Who M. Kim, Jean-François Lamarque, Danica L. Lombardozzi, William R. Wieder, and Stephen G. Yeager
Earth Syst. Dynam., 12, 1393–1411, https://doi.org/10.5194/esd-12-1393-2021, https://doi.org/10.5194/esd-12-1393-2021, 2021
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A large ensemble of simulations with 100 members has been conducted with the state-of-the-art CESM2 Earth system model, using historical and SSP3-7.0 forcing. Our main finding is that there are significant changes in the variance of the Earth system in response to anthropogenic forcing, with these changes spanning a broad range of variables important to impacts for human populations and ecosystems.
Henrique M. D. Goulart, Karin van der Wiel, Christian Folberth, Juraj Balkovic, and Bart van den Hurk
Earth Syst. Dynam., 12, 1503–1527, https://doi.org/10.5194/esd-12-1503-2021, https://doi.org/10.5194/esd-12-1503-2021, 2021
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Agriculture is sensitive to weather conditions and to climate change. We identify the weather conditions linked to soybean failures and explore changes related to climate change. Additionally, we build future versions of a historical extreme season under future climate scenarios. Results show that soybean failures are likely to increase with climate change. Future events with similar physical conditions to the extreme season are not expected to increase, but events with similar impacts are.
Kevin Sieck, Christine Nam, Laurens M. Bouwer, Diana Rechid, and Daniela Jacob
Earth Syst. Dynam., 12, 457–468, https://doi.org/10.5194/esd-12-457-2021, https://doi.org/10.5194/esd-12-457-2021, 2021
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This paper presents new estimates of future extreme weather in Europe, including extreme heat, extreme rainfall and meteorological drought. These new estimates were achieved by repeating model calculations many times, thereby reducing uncertainties of these rare events at low levels of global warming at 1.5 and 2 °C above
pre-industrial temperature levels. These results are important, as they help to assess which weather extremes could increase at moderate warming levels and where.
Anja Katzenberger, Jacob Schewe, Julia Pongratz, and Anders Levermann
Earth Syst. Dynam., 12, 367–386, https://doi.org/10.5194/esd-12-367-2021, https://doi.org/10.5194/esd-12-367-2021, 2021
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All state-of-the-art global climate models that contributed to the latest Coupled Model Intercomparison Project (CMIP6) show a robust increase in Indian summer monsoon rainfall that is even stronger than in the previous intercomparison (CMIP5). Furthermore, they show an increase in the year-to-year variability of this seasonal rainfall that crucially influences the livelihood of more than 1 billion people in India.
Joost Buitink, Lieke A. Melsen, and Adriaan J. Teuling
Earth Syst. Dynam., 12, 387–400, https://doi.org/10.5194/esd-12-387-2021, https://doi.org/10.5194/esd-12-387-2021, 2021
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Higher temperatures influence both evaporation and snow processes. These two processes have a large effect on discharge but have distinct roles during different seasons. In this study, we study how higher temperatures affect the discharge via changed evaporation and snow dynamics. Higher temperatures lead to enhanced evaporation but increased melt from glaciers, overall lowering the discharge. During the snowmelt season, discharge was reduced further due to the earlier depletion of snow.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Adam Hastie, Ronny Lauerwald, Philippe Ciais, Fabrice Papa, and Pierre Regnier
Earth Syst. Dynam., 12, 37–62, https://doi.org/10.5194/esd-12-37-2021, https://doi.org/10.5194/esd-12-37-2021, 2021
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We used a model of the Congo Basin to investigate the transfer of carbon (C) from land (vegetation and soils) to inland waters. We estimate that leaching of C to inland waters, emissions of CO2 from the water surface, and the export of C to the coast have all increased over the last century, driven by increasing atmospheric CO2 levels and climate change. We predict that these trends may continue through the 21st century and call for long-term monitoring of these fluxes.
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
Earth Syst. Dynam., 12, 17–35, https://doi.org/10.5194/esd-12-17-2021, https://doi.org/10.5194/esd-12-17-2021, 2021
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Motivated by the possible influence of rising temperatures, this study synthesises results from observations and climate models to explore trends (1900–2018) in eastern African (EA) drought measures. However, no discernible trends are found in annual soil moisture or precipitation. Positive trends in potential evaporation indicate that for irrigated regions more water is now required to counteract increased evaporation. Precipitation deficit is, however, the most useful indicator of EA drought.
Fabian von Trentini, Emma E. Aalbers, Erich M. Fischer, and Ralf Ludwig
Earth Syst. Dynam., 11, 1013–1031, https://doi.org/10.5194/esd-11-1013-2020, https://doi.org/10.5194/esd-11-1013-2020, 2020
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We compare the inter-annual variability of three single-model initial-condition large ensembles (SMILEs), downscaled with three regional climate models over Europe for seasonal temperature and precipitation, the number of heatwaves, and maximum length of dry periods. They all show good consistency with observational data. The magnitude of variability and the future development are similar in many cases. In general, variability increases for summer indicators and decreases for winter indicators.
Marianne T. Lund, Borgar Aamaas, Camilla W. Stjern, Zbigniew Klimont, Terje K. Berntsen, and Bjørn H. Samset
Earth Syst. Dynam., 11, 977–993, https://doi.org/10.5194/esd-11-977-2020, https://doi.org/10.5194/esd-11-977-2020, 2020
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Achieving the Paris Agreement temperature goals requires both near-zero levels of long-lived greenhouse gases and deep cuts in emissions of short-lived climate forcers (SLCFs). Here we quantify the near- and long-term global temperature impacts of emissions of individual SLCFs and CO2 from 7 economic sectors in 13 regions in order to provide the detailed knowledge needed to design efficient mitigation strategies at the sectoral and regional levels.
Kathrin Wehrli, Mathias Hauser, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 855–873, https://doi.org/10.5194/esd-11-855-2020, https://doi.org/10.5194/esd-11-855-2020, 2020
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The 2018 summer was unusually hot for large areas in the Northern Hemisphere, and heatwaves on three continents led to major impacts on agriculture and society. This study investigates storylines for the extreme 2018 summer, given the observed atmospheric circulation but different levels of background global warming. The results reveal a strong contribution by the present-day level of global warming and show a dramatic outlook for similar events in a warmer climate.
Rowan T. Sutton and Ed Hawkins
Earth Syst. Dynam., 11, 751–754, https://doi.org/10.5194/esd-11-751-2020, https://doi.org/10.5194/esd-11-751-2020, 2020
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Policy making on climate change routinely employs socioeconomic scenarios to sample the uncertainty in future forcing of the climate system, but the Intergovernmental Panel on Climate Change has not employed similar discrete scenarios to sample the uncertainty in the global climate response. Here, we argue that to enable risk assessments and development of robust policies this gap should be addressed, and we propose a simple methodology.
Andreas Geiges, Alexander Nauels, Paola Yanguas Parra, Marina Andrijevic, William Hare, Peter Pfleiderer, Michiel Schaeffer, and Carl-Friedrich Schleussner
Earth Syst. Dynam., 11, 697–708, https://doi.org/10.5194/esd-11-697-2020, https://doi.org/10.5194/esd-11-697-2020, 2020
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Current global mitigation ambition in the National Determined Contributions (NDCs) up to 2030 is insufficient to achieve the 1.5 °C long-term temperature limit. As governments are preparing new and updated NDCs for 2020, we address the question of what level of collective ambition is pivotal regarding the Paris Agreement goals. We provide estimates for global mean temperature increase by 2100 for different incremental NDC update scenarios and illustrate climate impacts under those scenarios.
Simone Tilmes, Douglas G. MacMartin, Jan T. M. Lenaerts, Leo van Kampenhout, Laura Muntjewerf, Lili Xia, Cheryl S. Harrison, Kristen M. Krumhardt, Michael J. Mills, Ben Kravitz, and Alan Robock
Earth Syst. Dynam., 11, 579–601, https://doi.org/10.5194/esd-11-579-2020, https://doi.org/10.5194/esd-11-579-2020, 2020
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This paper introduces new geoengineering model experiments as part of a larger model intercomparison effort, using reflective particles to block some of the incoming solar radiation to reach surface temperature targets. Outcomes of these applications are contrasted based on a high greenhouse gas emission pathway and a pathway with strong mitigation and negative emissions after 2040. We compare quantities that matter for societal and ecosystem impacts between the different scenarios.
Flavio Lehner, Clara Deser, Nicola Maher, Jochem Marotzke, Erich M. Fischer, Lukas Brunner, Reto Knutti, and Ed Hawkins
Earth Syst. Dynam., 11, 491–508, https://doi.org/10.5194/esd-11-491-2020, https://doi.org/10.5194/esd-11-491-2020, 2020
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Projections of climate change are uncertain because climate models are imperfect, future greenhouse gases emissions are unknown and climate is to some extent chaotic. To partition and understand these sources of uncertainty and make the best use of climate projections, large ensembles with multiple climate models are needed. Such ensembles now exist in a public data archive. We provide several novel applications focused on global and regional temperature and precipitation projections.
Florian Ehmele, Lisa-Ann Kautz, Hendrik Feldmann, and Joaquim G. Pinto
Earth Syst. Dynam., 11, 469–490, https://doi.org/10.5194/esd-11-469-2020, https://doi.org/10.5194/esd-11-469-2020, 2020
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This study presents a large novel data set of climate model simulations for central Europe covering the years 1900–2028 at a 25 km resolution. The focus is on intensive areal precipitation values. The data set is validated against observations using different statistical approaches. The results reveal an adequate quality in a statistical sense as well as some long-term variability with phases of increased and decreased heavy precipitation. The predictions of the near future show continuity.
Anton Laakso, Peter K. Snyder, Stefan Liess, Antti-Ilari Partanen, and Dylan B. Millet
Earth Syst. Dynam., 11, 415–434, https://doi.org/10.5194/esd-11-415-2020, https://doi.org/10.5194/esd-11-415-2020, 2020
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Geoengineering techniques have been proposed to prevent climate warming in the event of insufficient greenhouse gas emission reductions. Simultaneously, these techniques have an impact on precipitation, which depends on the techniques used, geoengineering magnitude, and background circumstances. We separated the independent and dependent components of precipitation responses to temperature, which were then used to explain the precipitation changes in the studied climate model simulations.
Monika J. Barcikowska, Sarah B. Kapnick, Lakshmi Krishnamurty, Simone Russo, Annalisa Cherchi, and Chris K. Folland
Earth Syst. Dynam., 11, 161–181, https://doi.org/10.5194/esd-11-161-2020, https://doi.org/10.5194/esd-11-161-2020, 2020
Anders Levermann, Ricarda Winkelmann, Torsten Albrecht, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, Philippe Huybrechts, Jim Jordan, Gunter Leguy, Daniel Martin, Mathieu Morlighem, Frank Pattyn, David Pollard, Aurelien Quiquet, Christian Rodehacke, Helene Seroussi, Johannes Sutter, Tong Zhang, Jonas Van Breedam, Reinhard Calov, Robert DeConto, Christophe Dumas, Julius Garbe, G. Hilmar Gudmundsson, Matthew J. Hoffman, Angelika Humbert, Thomas Kleiner, William H. Lipscomb, Malte Meinshausen, Esmond Ng, Sophie M. J. Nowicki, Mauro Perego, Stephen F. Price, Fuyuki Saito, Nicole-Jeanne Schlegel, Sainan Sun, and Roderik S. W. van de Wal
Earth Syst. Dynam., 11, 35–76, https://doi.org/10.5194/esd-11-35-2020, https://doi.org/10.5194/esd-11-35-2020, 2020
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We provide an estimate of the future sea level contribution of Antarctica from basal ice shelf melting up to the year 2100. The full uncertainty range in the warming-related forcing of basal melt is estimated and applied to 16 state-of-the-art ice sheet models using a linear response theory approach. The sea level contribution we obtain is very likely below 61 cm under unmitigated climate change until 2100 (RCP8.5) and very likely below 40 cm if the Paris Climate Agreement is kept.
Sabrina Hempel, Christoph Menz, Severino Pinto, Elena Galán, David Janke, Fernando Estellés, Theresa Müschner-Siemens, Xiaoshuai Wang, Julia Heinicke, Guoqiang Zhang, Barbara Amon, Agustín del Prado, and Thomas Amon
Earth Syst. Dynam., 10, 859–884, https://doi.org/10.5194/esd-10-859-2019, https://doi.org/10.5194/esd-10-859-2019, 2019
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Decreasing humidity and increasing wind speed regionally alleviate the heat load on farm animals, but future temperature rise considerably increases the heat stress risk. Livestock housed in open barns (or on pastures), such as dairy cattle, is particularly vulnerable. Without adaptation, heat waves will considerably reduce the gross margin of a livestock producer. Negative effects on productivity, health and animal welfare as well as increasing methane and ammonia emissions are expected.
Robert J. H. Dunn, Kate M. Willett, and David E. Parker
Earth Syst. Dynam., 10, 765–788, https://doi.org/10.5194/esd-10-765-2019, https://doi.org/10.5194/esd-10-765-2019, 2019
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Using a sub-daily dataset of in situ observations, we have performed a study to see how the distributions of temperatures and wind speeds have changed over the last 45 years. Changes in the location or shape of these distributions show how extreme temperatures or wind speeds have changed. Our results show that cool extremes are warming more rapidly than warm ones in high latitudes but that in other parts of the world the opposite is true.
Falko Ueckerdt, Katja Frieler, Stefan Lange, Leonie Wenz, Gunnar Luderer, and Anders Levermann
Earth Syst. Dynam., 10, 741–763, https://doi.org/10.5194/esd-10-741-2019, https://doi.org/10.5194/esd-10-741-2019, 2019
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We compute the global mean temperature increase at which the costs from climate-change damages and climate-change mitigation are minimal. This temperature is computed robustly around 2 degrees of global warming across a wide range of normative assumptions on the valuation of future welfare and inequality aversion.
Lise S. Graff, Trond Iversen, Ingo Bethke, Jens B. Debernard, Øyvind Seland, Mats Bentsen, Alf Kirkevåg, Camille Li, and Dirk J. L. Olivié
Earth Syst. Dynam., 10, 569–598, https://doi.org/10.5194/esd-10-569-2019, https://doi.org/10.5194/esd-10-569-2019, 2019
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Differences between a 1.5 and a 2.0 °C warmer global climate than 1850 conditions are discussed based on a suite of global atmosphere-only, fully coupled, and slab-ocean runs with the Norwegian Earth System Model. Responses, such as the Arctic amplification of global warming, are stronger with the fully coupled and slab-ocean configurations. While ice-free Arctic summers are rare under 1.5 °C warming in the slab-ocean runs, they are estimated to occur 18 % of the time under 2.0 °C warming.
David Gallego, Ricardo García-Herrera, Francisco de Paula Gómez-Delgado, Paulina Ordoñez-Perez, and Pedro Ribera
Earth Syst. Dynam., 10, 319–331, https://doi.org/10.5194/esd-10-319-2019, https://doi.org/10.5194/esd-10-319-2019, 2019
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By analysing old wind direction observations taken aboard sailing ships, it has been possible to build an index quantifying the moisture transport from the equatorial Pacific into large areas of Central America and northern South America starting in the late 19th century. This transport is deeply related to a low-level jet known as the Choco jet. Our results suggest that the seasonal distribution of the precipitation associated with this transport could have changed over the time.
Jens Heinke, Christoph Müller, Mats Lannerstad, Dieter Gerten, and Wolfgang Lucht
Earth Syst. Dynam., 10, 205–217, https://doi.org/10.5194/esd-10-205-2019, https://doi.org/10.5194/esd-10-205-2019, 2019
Filippo Giorgi, Francesca Raffaele, and Erika Coppola
Earth Syst. Dynam., 10, 73–89, https://doi.org/10.5194/esd-10-73-2019, https://doi.org/10.5194/esd-10-73-2019, 2019
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The paper revisits the critical issue of precipitation characteristics in response to global warming through a new analysis of global and regional climate projections and a summary of previous work. Robust responses are identified and the underlying processes investigated. Examples of applications are given, such as the evaluation of risks associated with extremes. The paper, solicited by the EGU executive office, is based on the 2018 EGU Alexander von Humboldt medal lecture by Filippo Giorgi.
Martin Rückamp, Ulrike Falk, Katja Frieler, Stefan Lange, and Angelika Humbert
Earth Syst. Dynam., 9, 1169–1189, https://doi.org/10.5194/esd-9-1169-2018, https://doi.org/10.5194/esd-9-1169-2018, 2018
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Sea-level rise associated with changing climate is expected to pose a major challenge for societies. Based on the efforts of COP21 to limit global warming to 2.0 °C by the end of the 21st century (Paris Agreement), we simulate the future contribution of the Greenland ice sheet (GrIS) to sea-level change. The projected sea-level rise ranges between 21–38 mm by 2100
and 36–85 mm by 2300. Our results indicate that uncertainties in the projections stem from the underlying climate data.
Rowan T. Sutton
Earth Syst. Dynam., 9, 1155–1158, https://doi.org/10.5194/esd-9-1155-2018, https://doi.org/10.5194/esd-9-1155-2018, 2018
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The purpose of the Intergovernmental Panel on Climate Change (IPCC) is to provide policy-relevant assessments of the scientific evidence about climate change. Policymaking necessarily involves risk assessments, so it is important that IPCC reports are designed accordingly. This paper proposes a specific idea, illustrated with examples, to improve the contribution of IPCC Working Group I to informing climate risk assessments.
Matthias Aengenheyster, Qing Yi Feng, Frederick van der Ploeg, and Henk A. Dijkstra
Earth Syst. Dynam., 9, 1085–1095, https://doi.org/10.5194/esd-9-1085-2018, https://doi.org/10.5194/esd-9-1085-2018, 2018
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We determine the point of no return (PNR) for climate change, which is the latest year to take action to reduce greenhouse gases to stay, with a certain probability, within thresholds set by the Paris Agreement. For a 67 % probability and a 2 K threshold, the PNR is the year 2035 when the share of renewable energy rises by 2 % per year. We show the impact on the PNR of the speed by which emissions are cut, the risk tolerance, climate uncertainties and the potential for negative emissions.
Martha M. Vogel, Jakob Zscheischler, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 1107–1125, https://doi.org/10.5194/esd-9-1107-2018, https://doi.org/10.5194/esd-9-1107-2018, 2018
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Climate change projections of temperature extremes are particularly uncertain in central Europe. We demonstrate that varying soil moisture–atmosphere feedbacks in current climate models leads to an enhancement of model differences; thus, they can explain the large uncertainties in extreme temperature projections. Using an observation-based constraint, we show that the strong drying and large increase in temperatures exhibited by models on the hottest day in central Europe are highly unlikely.
Jie Chen, Yujie Liu, Tao Pan, Yanhua Liu, Fubao Sun, and Quansheng Ge
Earth Syst. Dynam., 9, 1097–1106, https://doi.org/10.5194/esd-9-1097-2018, https://doi.org/10.5194/esd-9-1097-2018, 2018
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Results show that an additional 6.97 million people will be exposed to droughts in China under a 1.5 ºC target relative to reference period, mostly in the east of China. Demographic change is the primary contributor to exposure. Moderate droughts contribute the most to exposure among 3 grades of drought. Our simulations suggest that drought impact on people will continue to be a large threat to China under the 1.5 ºC target. It will be helpful in guiding adaptation and mitigation strategies.
Cited articles
An, S.-I. and Wang, B.: Interdecadal Change of the Structure of the ENSO Mode
and Its Impact on the ENSO Frequency, J. Climate, 13, 2044–2055,
https://doi.org/10.1175/1520-0442(2000)013<2044:ICOTSO>2.0.CO;2, 2000. a, b
Ashok, K., Behera, S. K., Rao, S. A., Weng, H., and Yamagata, T.: El Niño
Modoki and its possible teleconnection, J. Geophys. Res.-Oceans, 112, C11007, https://doi.org/10.1029/2006JC003798, 2007. a
Barnes, E. A., Hurrell, J. W., Ebert-Uphoff, I., Anderson, C., and Anderson,
D.: Viewing Forced Climate Patterns Through an AI Lens, Geophys. Res.
Lett., 46, 13389–13398, https://doi.org/10.1029/2019GL084944,
2019. a
Barnes, E. A., Toms, B., Hurrell, J. W., Ebert-Uphoff, I., Anderson, C., and
Anderson, D.: Indicator Patterns of Forced Change Learned by an Artificial
Neural Network, J. Adv. Model. Earth Sy., 12, e2020MS002195,
https://doi.org/10.1029/2020MS002195, 2020. a
Bellenger, H., Guilyardi, E., Leloup, J., Lengaigne, M., and Vialard, J.: ENSO
representation in climate models: from CMIP3 to CMIP5, Clim. Dynam., 42,
1999–2018, https://doi.org/10.1007/s00382-013-1783-z, 2014. a
Beobide-Arsuaga, G., Bayr, T., Reintges, A., and Latif, M.: Uncertainty of
ENSO-amplitude projections in CMIP5 and CMIP6 models, Clim. Dynam.,
56, 3875–3888, https://doi.org/10.1007/s00382-021-05673-4, 2021. a, b
Cai, W., Borlace, S., Lengaigne, M., van Rensch, P., Collins, M., Vecchi, G.,
Timmermann, A., Santoso, A., McPhaden, M. J., Wu, L., England, M. H., Wang,
G., Guilyardi, E., and Jin, F.-F.: Increasing frequency of extreme El Niño
events due to greenhouse warming, Nat. Clim. Change, 4, 111–116,
https://doi.org/10.1038/nclimate2100, 2014. a
Cai, W., Wang, G., Dewitte, B., Wu, L., Santoso, A., Takahashi, K., Yang, Y.,
Carréric, A., and McPhaden, M. J.: Increased variability of eastern Pacific
El Niño under greenhouse warming, Nature, 564, 201–206,
https://doi.org/10.1038/s41586-018-0776-9, 2018. a, b, c, d
Cai, W., Santoso, A., Collins, M., Dewitte, B., Karamperidou, C., Kug, J.-S.,
Lengaigne, M., McPhaden, M. J., Stuecker, M. F., Taschetto, A. S.,
Timmermann, A., Wu, L., Yeh, S.-W., Wang, G., Ng, B., Jia, F., Yang, Y.,
Ying, J., Zheng, X.-T., Bayr, T., Brown, J. R., Capotondi, A., Cobb, K. M.,
Gan, B., Geng, T., Ham, Y.-G., Jin, F.-F., Jo, H.-S., Li, X., Lin, X.,
McGregor, S., Park, J.-H., Stein, K., Yang, K., Zhang, L., and Zhong, W.:
Changing El Niño-Southern Oscillation in a warming climate, Nature Reviews
Earth & Environment, 2, 628–644, https://doi.org/10.1038/s43017-021-00199-z, 2021. a, b, c
Capotondi, A., Wittenberg, A. T., Newman, M., Lorenzo, E. D., Yu, J.-Y.,
Braconnot, P., Cole, J., Dewitte, B., Giese, B., Guilyardi, E., Jin, F.-F.,
Karnauskas, K., Kirtman, B., Lee, T., Schneider, N., Xue, Y., and Yeh, S.-W.:
Understanding ENSO Diversity, B. Am. Meteorol.
Soc., 96, 921–938, https://doi.org/10.1175/BAMS-D-13-00117.1, 2015. a, b
Capotondi, A., Wittenberg, A. T., Kug, J.-S., Takahashi, K., and McPhaden,
M. J.: ENSO Diversity, in: El Niño Southern Oscillation in a Changing Climate, edited by:
McPhaden, M. J., Santoso, A., and Cai, W., https://doi.org/10.1002/9781119548164.ch4, 2020. a, b, c, d
Chen, C., Cane, M. A., Wittenberg, A. T., and Chen, D.: ENSO in the CMIP5
Simulations: Life Cycles, Diversity, and Responses to Climate Change,
J. Climate, 30, 775–801, https://doi.org/10.1175/JCLI-D-15-0901.1, 2017a. a
Chen, L., Li, T., Yu, Y., and Behera, S. K.: A possible explanation for the
divergent projection of ENSO amplitude change under global warming, Clim.
Dynam., 49, 3799–3811, https://doi.org/10.1007/s00382-017-3544-x,
2017b. a
Chung, C. T. Y., Power, S. B., Arblaster, J. M., Rashid, H. A., and Roff,
G. L.: Nonlinear precipitation response to El Niño and global warming in the
Indo-Pacific, Clim. Dynam., 42, 1837–1856,
https://doi.org/10.1007/s00382-013-1892-8, 2014. a
Deser, C., Phillips, A. S., and Alexander, M. A.: Twentieth century tropical
sea surface temperature trends revisited, Geophys. Res. Lett., 37, L10701,
https://doi.org/10.1029/2010GL043321, 2010. a
Dieppois, B., Capotondi, A., Pohl, B., Chun, K. P., Monerie, P.-A., and Eden,
J.: ENSO diversity shows robust decadal variations that must be captured for
accurate future projections, Communications Earth & Environment, 2, 212,
https://doi.org/10.1038/s43247-021-00285-6, 2021. a, b, c
Fang, S.-W. and Yu, J.-Y.: Contrasting Transition Complexity Between El Niño
and La Niña: Observations and CMIP5/6 Models, Geophys. Res. Lett.,
47, 2020GL088926, https://doi.org/10.1029/2020GL088926, 2020. a
Feng, J., Lian, T., Ying, J., Li, J., and Li, G.: Do CMIP5 Models Show El Niño
Diversity?, J. Climate, 33, 1619–1641,
https://doi.org/10.1175/JCLI-D-18-0854.1, 2020. a
Fredriksen, H.-B., Berner, J., Subramanian, A. C., and Capotondi, A.: How Does
El Niño–Southern Oscillation Change Under Global Warming – A First Look at
CMIP6, Geophys. Res. Lett., 47, e2020GL090640,
https://doi.org/10.1029/2020GL090640, 2020. a, b
Freund, M. B., Henley, B. J., Karoly, D. J., McGregor, H. V., Abram, N. J., and
Dommenget, D.: Higher frequency of Central Pacific El Niño events in recent
decades relative to past centuries, Nat. Geosci., 12, 450–455,
https://doi.org/10.1038/s41561-019-0353-3, 2019. a, b, c
Giese, B. S. and Ray, S.: El Niño variability in simple ocean data
assimilation (SODA), 1871–2008, J. Geophys. Res.-Oceans,
116, C02024, https://doi.org/10.1029/2010JC006695, 2011. a
Gil, Y., Pierce, S. A., Babaie, H., Banerjee, A., Borne, K., Bust, G.,
Cheatham, M., Ebert-Uphoff, I., Gomes, C., Hill, M., Horel, J., Hsu, L.,
Kinter, J., Knoblock, C., Krum, D., Kumar, V., Lermusiaux, P., Liu, Y.,
North, C., Pankratius, V., Peters, S., Plale, B., Pope, A., Ravela, S.,
Restrepo, J., Ridley, A., Samet, H., Shekhar, S., Skinner, K., Smyth, P.,
Tikoff, B., Yarmey, L., and Zhang, J.: Intelligent Systems for Geosciences:
An Essential Research Agenda, Commun. ACM, 62, 76–84,
https://doi.org/10.1145/3192335, 2018. a
Guo, Y., Cao, X., Liu, B., and Peng, K.: El Niño Index Prediction Using Deep
Learning with Ensemble Empirical Mode Decomposition, Symmetry, 12, 893,
https://doi.org/10.3390/sym12060893, 2020. a
Ham, Y.-G., Jeong, Y., and Kug, J.-S.: Changes in Independency between Two
Types of El Niño Events under a Greenhouse Warming Scenario in CMIP5 Models,
J. Climate, 28, 7561–7575, https://doi.org/10.1175/JCLI-D-14-00721.1, 2015. a
Ham, Y.-G., Kim, J.-H., and Luo, J.-J.: Deep learning for multi-year ENSO
forecasts, Nature, 573, 568–572, https://doi.org/10.1038/s41586-019-1559-7, 2019. a
Haszpra, T., Herein, M., and Bódai, T.: Investigating ENSO and its teleconnections under climate change in an ensemble view – a new perspective, Earth Syst. Dynam., 11, 267–280, https://doi.org/10.5194/esd-11-267-2020, 2020. a
Hendon, H. H., Lim, E., Wang, G., Alves, O., and Hudson, D.: Prospects for
predicting two flavors of El Niño, Geophys. Res. Lett., 36, L19713,
https://doi.org/10.1029/2009GL040100, 2009. a
Hu, Z.-Z., Kumar, A., Ren, H.-L., Wang, H., L’Heureux, M., and Jin, F.-F.:
Weakened Interannual Variability in the Tropical Pacific Ocean since 2000,
J. Climate, 26, 2601–2613, https://doi.org/10.1175/JCLI-D-12-00265.1, 2013. a, b
Huang, B., Angel, W., Boyer, T., Cheng, L., Chepurin, G., Freeman, E., Liu, C.,
and Zhang, H.-M.: Evaluating SST Analyses with Independent Ocean Profile
Observations, J. Climate, 31, 5015–5030,
https://doi.org/10.1175/JCLI-D-17-0824.1, 2018. a
Huang, P. and Xie, S.-P.: Mechanisms of change in ENSO-induced tropical Pacific
rainfall variability in a warming climate, Nat. Geosci., 8, 922–926,
https://doi.org/10.1038/ngeo2571, 2015. a
Johnson, N. C.: How Many ENSO Flavors Can We Distinguish?, J. Climate,
26, 4816–4827, https://doi.org/10.1175/JCLI-D-12-00649.1, 2013. a
Kao, H.-Y. and Yu, J.-Y.: Contrasting Eastern-Pacific and Central-Pacific Types
of ENSO, J. Climate, 22, 615–632, https://doi.org/10.1175/2008JCLI2309.1,
2009. a, b, c
Karamperidou, C., Jin, F.-F., and Conroy, J. L.: The importance of ENSO
nonlinearities in tropical pacific response to external forcing, Clim.
Dynam., 49, 2695–2704, https://doi.org/10.1007/s00382-016-3475-y, 2017. a
Karpatne, A., Ebert-Uphoff, I., Ravela, S., Babaie, H. A., and Kumar,
V.: Machine Learning for the Geosciences: Challenges and Opportunities, IEEE
T. Knowl. Data En., 31, 1544–1554,
https://doi.org/10.1109/TKDE.2018.2861006, 2019. a
Kim, H.-M., webster, J., and J.A., C.: Impact of Shifting Patterns of Pacific
Ocean Warming on North Atlantic Tropical Cyclones, Science, 325, 77–80,
https://doi.org/10.1126/science.1174062, 2009. a
Kim, S. T., Cai, W., Jin, F.-F., Santoso, A., Wu, L., Guilyardi, E., and An,
S.-I.: Response of El Niño sea surface temperature variability to greenhouse
warming, Nat. Clim. Change, 4, 786–790, https://doi.org/10.1038/nclimate2326,
2014. a
Knutson, T. R., Manabe, S., and Gu, D.: Simulated ENSO in a Global Coupled
Ocean–Atmosphere Model: Multidecadal Amplitude Modulation and CO2
Sensitivity, J. Climate, 10, 138–161,
https://doi.org/10.1175/1520-0442(1997)010<0138:SEIAGC>2.0.CO;2, 1997. a
Kohyama, T., Hartmann, D. L., and Battisti, D. S.: La Niña–like Mean-State
Response to Global Warming and Potential Oceanic Roles, J. Climate,
30, 4207–4225, https://doi.org/10.1175/JCLI-D-16-0441.1, 2017. a, b, c
Kug, J.-S., Jin, F.-F., and An, S.-I.: Two Types of El Niño Events: Cold
Tongue El Niño and Warm Pool El Niño, J. Climate, 22, 1499–1515,
https://doi.org/10.1175/2008JCLI2624.1, 2009. a
Lemmon, D. E. and Karnauskas, K. B.: A metric for quantifying El Niño pattern
diversity with implications for ENSO-mean state interaction, Clim.
Dynam., 52, 7511–7523, https://doi.org/10.1007/s00382-018-4194-3, 2019. a
Liu, Y., Cobb, K. M., Song, H., Li, Q., Li, C.-Y., Nakatsuka, T., An, Z., Zhou,
W., Cai, Q., Li, J., Leavitt, S. W., Sun, C., Mei, R., Shen, C.-C., Chan,
M.-H., Sun, J., Yan, L., Lei, Y., Ma, Y., Li, X., Chen, D., and Linderholm,
H. W.: Recent enhancement of central Pacific El Niño variability relative to
last eight centuries, Nat. Commun., 8, 15386,
https://doi.org/10.1038/ncomms15386, 2017. a
Maher, N.: nicolamaher/classification: ENSO ML Classification – Maher, Tabarin, Milinski 2022 (v1.1.0), Zenodo [code], https://doi.org/10.5281/zenodo.7032576, 2022a. a
Maher, N.: Combining machine learning and SMILEs to classify, better understand, and project changes in ENSO events, MPG [code], https://pure.mpg.de/, last access: 29 August 2022b. a
Maher, N., Power, S., and Marotzke, J.: More accurate quantification of
model-to-model agreement in externally forced climatic responses over the
coming century, Nat. Commun., 12, 788, https://doi.org/10.1038/s41467-020-20635-w,
2021. a
Max-Planck-Institut für Meteorologie: MPI
Grand Ensemble, https://esgf-data.dkrz.de/projects/mpi-ge/, last access: 25 August 2022. a
McPhaden, M. J., Lee, T., and McClurg, D.: El Niño and its relationship to
changing background conditions in the tropical Pacific Ocean, Geophys. Res. Lett., 38, L15709, https://doi.org/10.1029/2011GL048275, 2011. a, b
Milinski, S., Maher, N., and Olonscheck, D.: How large does a large ensemble need to be?, Earth Syst. Dynam., 11, 885–901, https://doi.org/10.5194/esd-11-885-2020, 2020. a, b
NCAR/UCAR: Multi-Model Large Ensemble Archive, https://www.cesm.ucar.edu/projects/community-projects/MMLEA/, last access: 25 August 2022. a
Newman, M., Shin, S.-I., and Alexander, M. A.: Natural variation in ENSO
flavors, Geophys. Res. Lett., 38, L14705,
https://doi.org/10.1029/2011GL047658, 2011. a
NOAA Physical Sciences Laboratory: Gridded Climate Data, https://www.psl.noaa.gov/data/gridded/, last access: 25 August 2022. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J.,
Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.:
Scikit-learn: Machine Learning in Python, J. Mach. Learn.
Res., 12, 2825–2830, 2011. a, b, c
Planton, Y. Y., Guilyardi, E., Wittenberg, A. T., Lee, J., Gleckler, P. J.,
Bayr, T., McGregor, S., McPhaden, M. J., Power, S., Roehrig, R., Vialard, J.,
and Voldoire, A.: Evaluating Climate Models with the CLIVAR 2020 ENSO Metrics
Package, B. Am. Meteorol. Soc., 102, E193–E217,
https://doi.org/10.1175/BAMS-D-19-0337.1, 2021. a
Power, S., Delage, F., Chung, C., Kociuba, G., and Keay, K.: Robust
twenty-first-century projections of El Niño and related precipitation
variability, Nature, 502, 541–545, https://doi.org/10.1038/nature12580, 2013. a, b
Rasmusson, E. M. and Carpenter, T. H.: Variations in Tropical Sea Surface
Temperature and Surface Wind Fields Associated with the Southern
Oscillation/El Niño, Mon. Weather Rev., 110, 354–384,
https://doi.org/10.1175/1520-0493(1982)110<0354:VITSST>2.0.CO;2, 1982. a
Reichstein, M., Camps-Valls, G., Stevens, B., Jung, M., Denzler, J.,
Carvalhais, N., and Prabhat: Deep learning and process understanding for
data-driven Earth system science, Nature, 566, 195–204,
https://doi.org/10.1038/s41586-019-0912-1, 2019. a, b
Ren, H.-L. and Jin, F.-F.: Niño indices for two types of ENSO, Geophys. Res. Lett., 38, L04704, https://doi.org/10.1029/2010GL046031, 2011. a
Takahashi, K., Montecinos, A., Goubanova, K., and Dewitte, B.: ENSO regimes:
Reinterpreting the canonical and Modoki El Niño, Geophys. Res. Lett., 38, L10704, https://doi.org/10.1029/2011GL047364, 2011. a, b
Timmermann, A., An, S.-I., Kug, J.-S., Jin, F.-F., Cai, W., Capotondi, A.,
Cobb, K. M., Lengaigne, M., McPhaden, M. J., Stuecker, M. F., Stein, K.,
Wittenberg, A. T., Yun, K.-S., Bayr, T., Chen, H.-C., Chikamoto, Y., Dewitte,
B., Dommenget, D., Grothe, P., Guilyardi, E., Ham, Y.-G., Hayashi, M.,
Ineson, S., Kang, D., Kim, S., Kim, W., Lee, J.-Y., Li, T., Luo, J.-J.,
McGregor, S., Planton, Y., Power, S., Rashid, H., Ren, H.-L., Santoso, A.,
Takahashi, K., Todd, A., Wang, G., Wang, G., Xie, R., Yang, W.-H., Yeh,
S.-W., Yoon, J., Zeller, E., and Zhang, X.: El Niño-Southern Oscillation
complexity, Nature, 559, 535–545, https://doi.org/10.1038/s41586-018-0252-6, 2018. a
Toms, B. A., Barnes, E. A., and Ebert-Uphoff, I.: Physically Interpretable
Neural Networks for the Geosciences: Applications to Earth System
Variability, J. Adv. Model. Earth Sy., 12,
e2019MS002002, https://doi.org/10.1029/2019MS002002, 2020. a
Tseng, Y.-h., Huang, J.-H., and Chen, H.-C.: Improving the Predictability of
Two Types of ENSO by the Characteristics of Extratropical Precursors,
Geophys. Res. Lett., 49, e2021GL097190,
https://doi.org/10.1029/2021GL097190, 2022. a
Wang, B., Luo, X., Yang, Y.-M., Sun, W., Cane, M. A., Cai, W., Yeh, S.-W., and
Liu, J.: Historical change of El Niño properties sheds light on future
changes of extreme El Niño, P. Natl. Acad.
Sci. USA, 116, 22512–22517, https://doi.org/10.1073/pnas.1911130116, 2019. a, b, c, d
Watanabe, M., Kamae, Y., and Kimoto, M.: Robust increase of the equatorial
Pacific rainfall and its variability in a warmed climate, Geophys. Res.
Lett., 41, 3227–3232, https://doi.org/10.1002/2014GL059692, 2014. a
Wittenberg, A. T.: Are historical records sufficient to constrain ENSO
simulations?, Geophys. Res. Lett., 36, L12702, https://doi.org/10.1029/2009GL038710,
2009. a, b, c
World Climate Research ProgrammeWCRP Coupled Model Intercomparison Project (Phase 6), https://esgf-data.dkrz.de/projects/cmip6-dkrz/, last access: 25 August 2022. a
Yeh, S.-W., Kug, J.-S., Dewitte, B., Kwon, M.-H., and Kirtman, B. P. Jin,
F.-F.: El Niño in a changing climate, Nature, 461, 511–514,
https://doi.org/10.1038/nature08316, 2009. a, b, c
Yeh, S.-W., Kirtman, B. P., Kug, J.-S., Park, W., and Latif, M.: Natural
variability of the central Pacific El Niño event on multi-centennial
timescales, Geophys. Res. Lett., 38, L02704,
https://doi.org/10.1029/2010GL045886, 2011. a
Yeh, S.-W., Kug, J.-S., and S-I., A.: Recent progress on two types of El
Niño: Observations, dynamics, and future changes, Asia-Pac. J.
Atmos. Sci., 50, 69–81, https://doi.org/10.1007/s13143-014-0028-3, 2014. a
Yu, J.-Y. and Fang, S.-W.: The Distinct Contributions of the Seasonal
Footprinting and Charged-Discharged Mechanisms to ENSO Complexity,
Geophys. Res. Lett., 45, 6611–6618,
https://doi.org/10.1029/2018GL077664, 2018. a
Yu, J.-Y. and Kim, S. T.: Identification of Central-Pacific and Eastern-Pacific
types of ENSO in CMIP3 models, Geophys. Res. Lett., 37, L15705,
https://doi.org/10.1029/2010GL044082, 2010. a
Yun, K.-S., Lee, J.-Y., Timmermann, A., Stein, K., Stuecker, M. F., Fyfe,
J. C., and Chung, E.-S.: Increasing ENSO-rainfall variability due to changes
in future tropical temperature-rainfall relationship, Communications Earth &
Environment, 2, 43, https://doi.org/10.1038/s43247-021-00108-8, 2021. a
Zheng, X.-T., Hui, C., and Yeh, S.-W.: Response of ENSO amplitude to global
warming in CESM large ensemble: uncertainty due to internal variability,
Clim. Dynam., 50, 4019–4035, https://doi.org/10.1007/s00382-017-3859-7, 2017. a
Short summary
El Niño events occur as two broad types: eastern Pacific (EP) and central Pacific (CP). EP and CP events differ in strength, evolution, and in their impacts. In this study we create a new machine learning classifier to identify the two types of El Niño events using observed sea surface temperature data. We apply our new classifier to climate models and show that CP events are unlikely to change in frequency or strength under a warming climate, with model disagreement for EP events.
El Niño events occur as two broad types: eastern Pacific (EP) and central Pacific (CP). EP and...
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